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This study examines through a systematic review, the reference services rendered in academic libraries using artificial intelligence (AI) and by collecting data through environmental scanning. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring the application of artificial intelligence for reference services in academic libraries. Data were collected from Web of Science, Scopus, and LISA databases. Following the rigorous/established selection process, a total of thirty five articles were finally selected, reviewed and analyzed. Thirty five papers were identified, analyzed and summarized on the subject relating to the application of AI and the methods which are most often used. The findings demonstrate that university libraries in Canada and China are leading in the deployment of AI for reference services. The AI techniques used mostly in the scanned university libraries are self-directed learning and natural language processing techniques; while the challenges of using AI for reference services are the problem of quality intelligence, linguistic style, privacy, a threat to intellectual freedom, bias, and cost; inadequate experts, poor network, poor training and lack of innovation, and limited knowledge about the technology. The study indicates university libraries take into account implementing AI for reference services. [ABSTRACT FROM AUTHOR]